Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the behavioral disclosure burden. It does well by stating that results are non-sensitive aggregates only (no personal data) and that the tool returns both a ready-to-quote summary and underlying counts. This gives an agent a clear expectation of output shape and data sensitivity.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the action and resource, and the additional detail is packed into a parenthetical list followed by two concise clarifying sentences. It is slightly dense, but every phrase adds information and nothing feels like filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no parameters, no output schema, and no annotations, the description provides adequate context: purpose, content scope, return shape, and a data-safety note. It could be more complete with explicit guidance on when to prefer this tool over related siblings, but it is strong overall.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so there is nothing for the description to document about individual inputs. The description still adds value by clarifying what the returned statistics represent, which is sufficient for a parameterless tool.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Get IA-Asso PLATFORM stats.' It then enumerates exactly what those stats cover (active associations, RUP recognition, Journal Officiel records, coverage, MCP+API positioning), making the tool's purpose unmistakable and distinguishable from association-level or department-level siblings like get_association and get_department_stats.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly implies when this tool is appropriate: when a user wants global, public, platform-wide aggregate stats. However, it does not explicitly state when not to use it or mention alternatives such as get_department_stats or get_france_overview, leaving the routing decision partly to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.